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Adept traffic models are critical to both planning and closed-loop simulation for autonomous vehicles (AV), and key design objectives include accuracy, diverse multimodal behaviors, interpretability, and downstream compatibility.
Search-based path planning with homotopy class constraints
S. Bhattacharya · 2010
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Topological constraints in search-based robot path planning
S. Bhattacharya, M. Likhachev, and V. Kumar · 2012
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Auto-encoding variational bayes, 2013
D. P. Kingma and M. Welling · 2013
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Social LSTM: Human trajectory prediction in crowded spaces
A. Alahi, K. Goel, V. Ramanathan, A. Robicquet, L. Fei-Fei, and S. Savarese · 2016
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Tree-structured policy planning with learned behavior models
Y. Chen, P. Karkus, B. Ivanovic, X. Weng, and M. Pavone · 2016
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Path homotopy invariants and their application to optimal trajectory planning
S. Bhattacharya and R. Ghrist · 2017
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Categorial reparameterization with gumbel-softmax
E. Jang, S. Gu, and B. Poole · 2017
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Computing possible driving corridors for automated vehicles
S. Söntges and M. Althoff · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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IntentNet: Learning to predict intention from raw sensor data
Sergio Casas, Wenjie Luo, and Raquel Urtasun · 2018
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MultiPath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction
Y. Chai, B. Sapp, M. Bansal, and D. Anguelov · 2019
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Multimodal trajectory predictions for autonomous driving using deep convolutional networks
H. Cui, V. Radosavljevic, F. Chou, T. Lin, T. Nguyen, T. Huang, J. Schneider, and N. Djuric · 2019
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PRECOG: Prediction conditioned on goals in visual multi-agent settings
Nicholas Rhinehart, Rowan McAllister, Kris Kitani, and Sergey Levine · 2019
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Multiple futures prediction
Y. C. Tang and R. Salakhutdinov · 2019
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Waymo Open Dataset: An autonomous driving dataset
Waymo · 2019
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Language models are few-shot learners
T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, et al · 2020
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nuScenes: A multimodal dataset for autonomous driving
Holger Caesar, Varun Bankiti, Alex H. Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom · 2020
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Implicit latent variable model for scene-consistent motion forecasting
S. Casas, C. Gulino, S. Suo, K. Luo, R. Liao, and R. Urtasun · 2020
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Vectornet: Encoding hd maps and agent dynamics from vectorized representation
J. Gao, C. Sun, H. Zhao, Y. Shen, D. Anguelov, C. Li, and C. Schmid · 2020
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Learning lane graph representations for motion forecasting
M. Liang, B. Yang, R. Hu, Y. Chen, R. Liao, S. Feng, and R. Urtasun · 2020
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PnPNet: End-to-end perception and prediction with tracking in the loop
M. Liang, B. Yang, W. Zeng, Y. Chen, R. Hu, S. Casas, and R. Urtasun · 2020
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Trajectron++: Dynamically-feasible trajectory forecasting with heterogeneous data
T. Salzmann, B. Ivanovic, P. Chakravarty, and M. Pavone · 2020
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Spatio-temporal graph transformer networks for pedestrian trajectory prediction
C. Yu, X. Ma, J. Ren, H. Zhao, and S. Yi · 2020
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Dlow: Diversifying latent flows for diverse human motion prediction
Y. Yuan and K. Kitani · 2020
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TNT: Target-driveN Trajectory Prediction
H. Zhao, J. Gao, T. Lan, C. Sun, B. Sapp, B. Varadarajan, Y. Shen, Y. Shen, Y. Chai, C. Schmid, C. Li, and D. Anguelov · 2020
Mtr-a: 1st place solution for 2022 waymo open dataset challenge–motion prediction
Shaoshuai Shi, Li Jiang, Dengxin Dai, and Bernt Schiele · 2022
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Multipath++: Efficient information fusion and trajectory aggregation for behavior prediction
B. Varadarajan, A. Hefny, A. Srivastava, K. S Refaat, N. Nayakanti, A. Cornman, K. Chen, B. Douillard, Chi P. Lam, D. Anguelov, et al · 2022
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Ltp: Lane-based trajectory prediction for autonomous driving
J. Wang, T. Ye, Z. Gu, and J. Chen · 2022
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Bits: Bi-level imitation for traffic simulation
D. Xu, Y. Chen, B. Ivanovic, and M. Pavone · 2022
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Sparks of artificial general intelligence: Early experiments with gpt-4
S. Bubeck, V. Chandrasekaran, R. Eldan, J. Gehrke, E. Horvitz, E. Kamar, P. Lee, Y. Lee, Y. Li, S. Lundberg, et al · 2023
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Gisnet: Graph-based information sharing network for vehicle trajectory prediction
Z. Zhao, H. Fang, Z. Jin, and Q. Qiu · 2020
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nuplan: A closed-loop ml-based planning benchmark for autonomous vehicles
H. Caesar, J. Kabzan, K. Tan, W. Fong, E. Wolff, A. Lang, L. Fletcher, O. Beijbom, and S. Omari · 2021
Cited alongside, same era.
DenseTNT: End-to-end trajectory prediction from dense goal sets
J. Gu, C. Sun, and H. Zhao · 2021
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Scene transformer: A unified architecture for predicting multiple agent trajectories
J. Ngiam, B. Caine, V. Vasudevan, Z. Zhang, H. Chiang, J. Ling, R. Roelofs, A. Bewley, C. Liu, A. Venugopal, D. Weiss, B. Sapp, Z. Chen, and J. Shlens · 2021
Cited alongside, same era.
Multimodal trajectory prediction via topological invariance for navigation at uncontrolled intersections
J. Roh, C. Mavrogiannis, R. Madan, D. Fox, and S. Srinivasa · 2021
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Joint intention and trajectory prediction based on transformer
Z. Sui, Y. Zhou, X. Zhao, A. Chen, and Y. Ni · 2021
Cited alongside, same era.
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Driving with llms: Fusing object-level vector modality for explainable autonomous driving
Long Chen, Oleg Sinavski, Jan Hünermann, Alice Karnsund, Andrew James Willmott, Danny Birch, Daniel Maund, and Jamie Shotton · 2023
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Interactive joint planning for autonomous vehicles
Y. Chen, S. Veer, P. Karkus, and M. Pavone · 2023
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Gorela: Go relative for viewpoint-invariant motion forecasting
A. Cui, S. Casas, K. Wong, S. Suo, and R. Urtasun · 2023
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Drivellm: Charting the path toward full autonomous driving with large language models
Yaodong Cui, Shucheng Huang, Jiaming Zhong, Zhenan Liu, Yutong Wang, Chen Sun, Bai Li, Xiao Wang, and Amir Khajepour · 2023
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Palm-e: An embodied multimodal language model
D. Driess, F. Xia, M. SM Sajjadi, C. Lynch, A. Chowdhery, B. Ichter, A. Wahid, J. Tompson, Q. Vuong, T. Yu, et al · 2023
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Gaia-1: A generative world model for autonomous driving
Anthony Hu, Lloyd Russell, Hudson Yeo, Zak Murez, George Fedoseev, Alex Kendall, Jamie Shotton, and Gianluca Corrado · 2023
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Hdgt: Heterogeneous driving graph transformer for multi-agent trajectory prediction via scene encoding
X. Jia, P. Wu, L. Chen, Y. Liu, H. Li, and J. Yan · 2023
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Jfp: Joint future prediction with interactive multi-agent modeling for autonomous driving
W. Luo, C. Park, A. Cornman, B. Sapp, and D. Anguelov · 2023
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Gpt-driver: Learning to drive with gpt
Jiageng Mao, Yuxi Qian, Hang Zhao, and Yue Wang · 2023
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Wayformer: Motion forecasting via simple & efficient attention networks
N. Nayakanti, R. Al-Rfou, A. Zhou, K. Goel, K. S Refaat, and B. Sapp · 2023
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Motionlm: Multi-agent motion forecasting as language modeling
A. Seff, B. Cera, D. Chen, M. Ng, A. Zhou, N. Nayakanti, K. S Refaat, R. Al-Rfou, and B. Sapp · 2023
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Languagempc: Large language models as decision makers for autonomous driving
Hao Sha, Yao Mu, Yuxuan Jiang, Li Chen, Chenfeng Xu, Ping Luo, Shengbo Eben Li, Masayoshi Tomizuka, Wei Zhan, and Mingyu Ding · 2023
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Yun Tang, Antonio A Bruto da Costa, Jason Zhang, Irvine Patrick, Siddartha Khastgir, and Paul Jennings · 2023
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Llama: Open and efficient foundation language models
H. Touvron, T. Lavril, G. Izacard, X. Martinet, M. Lachaux, T. Lacroix, B. Rozière, N. Goyal, E. Hambro, F. Azhar, et al · 2023
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